Progress and Prospects in EEG-Based Brain-Computer Interface: Clinical Applications in Neurorehabilitation
DOI:
https://doi.org/10.12970/2308-8354.2013.01.01.4Keywords:
Rehabilitation robot, Stability and smoothness, Dynamic interpolation, Impedance control.Abstract
Several patients are no longer able to communicate effectively or even interact with the outside world in ways that most of us do it. For instance, severe cases astetraplegic or post-stroke patients are literally 'locked in' their bodies, unable to exert any motor control after a spinal cord injury or a brainstem stroke, requiring alternative methods of communication and control. However, in the near future, their brains may offer them a way out. EEG-based brain-computer interface (BCI) is the technique utilized to measure brain activity and by the way that different brain signals are translated into commands that control an effector (e.g., controlling a spelling system via eye movements). Here,we aim to review the basic concepts of EEG-based BCI and the main advances in communication, in motor control restoration and in downregulation of cortical activitythat seem to be relevant for clinical applications in the coming years forneurorehabilitation of severely limited patients. It allows brain-derived communication in patients with amyotrophic lateral sclerosis and motor control restoration in patients after spinal cord injury and stroke. In addition, epilepsy and attention deficit and hyperactive disorder patients were able to downregulate their cortical activity. Owing to the rapid progression of EEG-based BCI research over the last few years and the swift ascent of computer processing speeds and signal analysis techniques, we suggest that emerging ideas related to clinical neurorehabilitation of severely limited patients will generate viable clinical applications in the near future. Keywords: Amyotrophic Lateral Sclerosis, attention deficit and hyperactive disorder, EEG-based brain-computer interface, epilepsy, neurorehabilitation, spinal cord, stroke.References
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